Maintaining Equitable and Inclusive Classroom Communities Online During the COVID-19 Pandemic
Bibliographic record
Abstract
This paper explores the ways in which face-to-face classroom communities were disrupted and/or transformed by the move to online platforms and the effect of this disruption on equitable access to a quality education. Quality education is defined as engaged pedagogy, where students learn to interact with other students and engage with ideas in a way that promotes their ability to be part of a community while still feeling free to disagree with, critique, and take care of each other. To examine the extent to which such communities were created when schooling migrated online during the pandemic, this paper examines online schooling communities in terms of sense of belonging, trust, shared purpose, and quality of interactions. The analysis of the experiences of 11 teachers in Ontario, Canada, whose face-to-face classes were moved to online formats, establishes that equity was one of the first casualties of the change, with the most vulnerable students facing disproportionate academic, psychological, and social consequences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".